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System Design Guide for Software Professionals

You're reading from   System Design Guide for Software Professionals Build scalable solutions – from fundamental concepts to cracking top tech company interviews

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805124993
Length 384 pages
Edition 1st Edition
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Authors (2):
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Dhirendra Sinha Dhirendra Sinha
Author Profile Icon Dhirendra Sinha
Dhirendra Sinha
Tejas Chopra Tejas Chopra
Author Profile Icon Tejas Chopra
Tejas Chopra
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Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1: Foundations of System Design
2. Chapter 1: Basics of System Design FREE CHAPTER 3. Chapter 2: Distributed System Attributes 4. Chapter 3: Distributed Systems Theorems and Data Structures 5. Part 2: Core Components of Distributed Systems
6. Chapter 4: Distributed Systems Building Blocks: DNS, Load Balancers, and Application Gateways 7. Chapter 5: Design and Implementation of System Components –Databases and Storage 8. Chapter 6: Distributed Cache 9. Chapter 7: Pub/Sub and Distributed Queues 10. Part 3: System Design in Practice
11. Chapter 8: Design and Implementation of System Components: API, Security, and Metrics 12. Chapter 9: System Design – URL Shortener 13. Chapter 10: System Design – Proximity Service 14. Chapter 11: Designing a Service Like Twitter 15. Chapter 12: Designing a Service Like Instagram 16. Chapter 13: Designing a Service Like Google Docs 17. Chapter 14: Designing a Service Like Netflix 18. Chapter 15: Tips for Interviewees 19. Chapter 16: System Design Cheat Sheet 20. Index

Summary

In this chapter, we explored the system design of a Netflix-like platform, covering various aspects such as functional and non-functional requirements, data modeling, capacity estimation, high-level architecture, and the design of key components, such as the Video Service, User Service, Recommendation Service, and CDN.

We started by defining the core features and functionalities that our platform should support, ensuring a comprehensive and user-centric streaming experience. We then discussed the non-functional requirements, emphasizing the importance of scalability, performance, reliability, and security.

To handle the massive amount of data and traffic generated by millions of users, we delved into data modeling and capacity estimation. We designed a data model that captures the essential entities and relationships, and we performed calculations to estimate the storage, bandwidth, and processing requirements of our platform.

Based on these requirements and estimations...

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